Project BIOL 3100

Noah Christensen

Home | About Me | Final Project

Geologic maps serve as a valuable tool in resource exploration.Traditional mapping is characterized by time-intensive and high-cost fieldwork, but through multispectral and hyperspectral remotely sensed images it is possible to map extensive areas instantly.

Being able to calculate areas of interest for potential hydrothermal alteration zones can be extremely useful in determining the history and available resources geologically through remote sensing.

add in Geologic background of Marysvale volcanics

Background

Bandpass Filters

Bandpass filters are essential for collection and analysis of satellite imagery, they allow specific ranges of electromagnetic wavelengths, or bands, to be transmitted while blocking others.

FWHM

Full Width Half Mass (FWHM) is an important concept for understanding how different bands are delineated.

The graph below visualizes the idea of FWHM. Each band in a spectral device only takes in a specific range of wavelengths, often the wavelength for each band is just denoted as the peak, but in reality each sensor is collecting a range of wavelengths. This is determined by denoting the FWHM as the area between the 50% transmittance on both sides of the curve.

Landsat 8, Hyperion, and ASTER bands

In this plot you can see all the bands for Landsat 8, Hyperion, and ASTER. With their FWHM denoted as boxes. Its important to point out how Landsat 8 does have a band in the Short Wave Infrared (SWIR), but the FWHM is wide and this means that any SWIR data saved for this band could be attributed to any wavelength inside of the FWHM.

Location of research

Geologic Map

Classification of Land Cover

It is important to eliminate areas that are not exposed soil or rock to accurately map alteration zones.

Land cover classification over North America is available for download from the National Land Cover Database. 2021 classification was used as that is the most recent year available.

The Landsat imagery tested against the NLCD was collected Oct 19th, 2023.

NLCD has more specific delineations of landcover, I. combined this. and reduced the dimensions to three classifications: Barren, Snow, and Vegetation

Class 1: Barren Class 2: Snow Class 3: Vegetation

## Confusion Matrix and Statistics
## 
##           Reference
## Prediction      1      2      3
##          1 253987     95 280759
##          2  10001     37    607
##          3  55484    176 399263
## 
## Overall Statistics
##                                          
##                Accuracy : 0.653          
##                  95% CI : (0.6521, 0.654)
##     No Information Rate : 0.6804         
##     P-Value [Acc > NIR] : 1              
##                                          
##                   Kappa : 0.3326         
##                                          
##  Mcnemar's Test P-Value : <2e-16         
## 
## Statistics by Class:
## 
##                      Class: 1  Class: 2 Class: 3
## Sensitivity            0.7950 1.201e-01   0.5866
## Specificity            0.5875 9.894e-01   0.8259
## Pos Pred Value         0.4749 3.476e-03   0.8776
## Neg Pred Value         0.8593 9.997e-01   0.4842
## Prevalence             0.3193 3.079e-04   0.6804
## Detection Rate         0.2539 3.698e-05   0.3991
## Detection Prevalence   0.5346 1.064e-02   0.4547
## Balanced Accuracy      0.6913 5.548e-01   0.7063
## Accuracy: 0.6530199
## Kappa: 0.3325882

Landsat

Landsat is an ongoing satellite imagery collection system with a recurrence interval of 8 days. Now lets make some plots of different mineral groups:

Iron Oxides

Iron Oxides mapping can be created using Band4/Band2

Clay and Hydroxyl

Hydroxyl mineral mapping can be created using Band6/Band7

Ferrous

Ferrous (iron minerals) can be mapped using Band6/Band5

Sabins Ratio

A Sabins Ratio plot can be created by combining these three plots into an RGB profile.

Iron-oxide dominated areas are mapped in pink, clay and hydroxyl minerals in green and ferrous minerals are discriminated in blue. Hydrothermal alteration areas are represented by the association of green-pink or yellow zones.

ASTER

Calcite Index

Calcite minerals can be mapped using (b6/b8) * (b9/b8)

Kaolinite, sericite, chlorite, and epidote index

Kaolinite, sericite, chlorite, and epidote minerals can be mapped using (b7+b9)/b8

Alteration zones